Navigating the artificial intelligence revolution in neuro-oncology: A multidisciplinary viewpoint

This comprehensive review presents the role of artificial intelligence (AI), machine learning (ML), and deep learning (DL) in neuro-oncology, focussing their groundbreaking impact on the field. It gives a historical overview of AI's evolution in area of neuro-oncology, representing its progress from basic data management to high-level predictive analytics that now significantly makes personalized treatment approaches. Further, This study examines various ML based methods that emphasize brain tumor classification, genetic profiling, and individualized care plans proposals, which basically reflects the shift towards precision medicine. This paper also highlights, developments in DL particularly in the development of neuro-imaging analysis, which has significantly guided surgical planning and radiation therapy for improved patient outcomes. Through various case studies, the paper presents recent breakthroughs where AI interventions have noticeably enhanced the treatment of neuro-oncological conditions. Moreover, It also addresses the ethical considerations encompassing the use of automated decision-making tools, emphasizing the need for ethical governance in AI deployment. By integrating multidisciplinary perspectives, the study underscores the collaborative effort between clinicians, data scientists, and ethicists, which is very crucial for the ethical and effective implementation of AI in current clinical practice. The main aim of discussion is to equip neurooncologists/sergeons and doctors with understandings into sustainable AI adoption which ensures that AI's path in neuro-oncology aligns with both clinical needs for personalized medicine and ethical standards. This paper concludes by outlining considered methods and frameworks for the future integration of AI in neuro-oncology, predicting trends, and preparing to meet the challenges ahead. © 2024